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Postgres FD Implementation
Commit 4e57668d authored by Tom Lane's avatar Tom Lane
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Create a selectivity estimation function for the text search @@ operator. 

Jan Urbanski
parent e2b7d0c6
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Showing with 463 additions and 30 deletions
doc/src/sgml/catalogs.sgml
View file @ 4e57668d
<!-- $PostgreSQL: pgsql/doc/src/sgml/catalogs.sgml,v 2.174 2008/09/15 18:43:41 tgl Exp $ -->
<!-- $PostgreSQL: pgsql/doc/src/sgml/catalogs.sgml,v 2.175 2008/09/19 19:03:40 tgl Exp $ -->
<!--
Documentation of the system catalogs, directed toward PostgreSQL developers
-->
......@@ -6664,6 +6664,9 @@
A list of the frequencies of the most common values or elements,
i.e., number of occurrences of each divided by total number of rows.
(NULL when <structfield>most_common_vals</structfield> is.)
For some datatypes such as <type>tsvector</>, it can also store some
additional information, making it longer than the
<structfield>most_common_vals</> array.
</entry>
</row>
......
src/backend/tsearch/Makefile
View file @ 4e57668d
......@@ -4,7 +4,7 @@
#
# Copyright (c) 2006-2008, PostgreSQL Global Development Group
#
# $PostgreSQL: pgsql/src/backend/tsearch/Makefile,v 1.7 2008/07/14 00:51:45 tgl Exp $
# $PostgreSQL: pgsql/src/backend/tsearch/Makefile,v 1.8 2008/09/19 19:03:40 tgl Exp $
#
#-------------------------------------------------------------------------
subdir = src/backend/tsearch
......@@ -19,7 +19,7 @@ DICTFILES=synonym_sample.syn thesaurus_sample.ths hunspell_sample.affix \
OBJS = ts_locale.o ts_parse.o wparser.o wparser_def.o dict.o \
dict_simple.o dict_synonym.o dict_thesaurus.o \
dict_ispell.o regis.o spell.o \
to_tsany.o ts_typanalyze.o ts_utils.o
to_tsany.o ts_selfuncs.o ts_typanalyze.o ts_utils.o
include $(top_srcdir)/src/backend/common.mk
......
src/backend/tsearch/ts_selfuncs.c 0 → 100644
View file @ 4e57668d
/*-------------------------------------------------------------------------
*
* ts_selfuncs.c
* Selectivity estimation functions for text search operators.
*
* Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
*
*
* IDENTIFICATION
* $PostgreSQL: pgsql/src/backend/tsearch/ts_selfuncs.c,v 1.1 2008/09/19 19:03:40 tgl Exp $
*
*-------------------------------------------------------------------------
*/
#include "postgres.h"
#include "catalog/pg_statistic.h"
#include "catalog/pg_type.h"
#include "miscadmin.h"
#include "nodes/nodes.h"
#include "tsearch/ts_type.h"
#include "utils/lsyscache.h"
#include "utils/selfuncs.h"
#include "utils/syscache.h"
/*
* The default text search selectivity is chosen to be small enough to
* encourage indexscans for typical table densities. See selfuncs.h and
* DEFAULT_EQ_SEL for details.
*/
#define DEFAULT_TS_MATCH_SEL 0.005
/* lookup table type for binary searching through MCELEMs */
typedef struct
{
text *element;
float4 frequency;
} TextFreq;
/* type of keys for bsearch'ing through an array of TextFreqs */
typedef struct
{
char *lexeme;
int length;
} LexemeKey;
static Selectivity tsquerysel(VariableStatData *vardata, Datum constval);
static Selectivity mcelem_tsquery_selec(TSQuery query,
Datum *mcelem, int nmcelem,
float4 *numbers, int nnumbers);
static Selectivity tsquery_opr_selec(QueryItem *item, char *operand,
TextFreq *lookup, int length, float4 minfreq);
static int compare_lexeme_textfreq(const void *e1, const void *e2);
/*
* tsmatchsel -- Selectivity of "@@"
*
* restriction selectivity function for tsvector @@ tsquery and
* tsquery @@ tsvector
*/
Datum
tsmatchsel(PG_FUNCTION_ARGS)
{
PlannerInfo *root = (PlannerInfo *) PG_GETARG_POINTER(0);
#ifdef NOT_USED
Oid operator = PG_GETARG_OID(1);
#endif
List *args = (List *) PG_GETARG_POINTER(2);
int varRelid = PG_GETARG_INT32(3);
VariableStatData vardata;
Node *other;
bool varonleft;
Selectivity selec;
/*
* If expression is not variable = something or something = variable, then
* punt and return a default estimate.
*/
if (!get_restriction_variable(root, args, varRelid,
&vardata, &other, &varonleft))
PG_RETURN_FLOAT8(DEFAULT_TS_MATCH_SEL);
/*
* Can't do anything useful if the something is not a constant, either.
*/
if (!IsA(other, Const))
{
ReleaseVariableStats(vardata);
PG_RETURN_FLOAT8(DEFAULT_TS_MATCH_SEL);
}
/*
* The "@@" operator is strict, so we can cope with NULL right away
*/
if (((Const *) other)->constisnull)
{
ReleaseVariableStats(vardata);
PG_RETURN_FLOAT8(0.0);
}
/*
* OK, there's a Var and a Const we're dealing with here. We need the Var
* to be a TSVector (or else we don't have any useful statistic for it).
* We have to check this because the Var might be the TSQuery not the
* TSVector.
*/
if (vardata.vartype == TSVECTOROID)
{
/* tsvector @@ tsquery or the other way around */
Assert(((Const *) other)->consttype == TSQUERYOID);
selec = tsquerysel(&vardata, ((Const *) other)->constvalue);
}
else
{
/* The Var is something we don't have useful statistics for */
selec = DEFAULT_TS_MATCH_SEL;
}
ReleaseVariableStats(vardata);
CLAMP_PROBABILITY(selec);
PG_RETURN_FLOAT8((float8) selec);
}
/*
* tsmatchjoinsel -- join selectivity of "@@"
*
* join selectivity function for tsvector @@ tsquery and tsquery @@ tsvector
*/
Datum
tsmatchjoinsel(PG_FUNCTION_ARGS)
{
/* for the moment we just punt */
PG_RETURN_FLOAT8(DEFAULT_TS_MATCH_SEL);
}
/*
* @@ selectivity for tsvector var vs tsquery constant
*/
static Selectivity
tsquerysel(VariableStatData *vardata, Datum constval)
{
Selectivity selec;
if (HeapTupleIsValid(vardata->statsTuple))
{
TSQuery query;
Form_pg_statistic stats;
Datum *values;
int nvalues;
float4 *numbers;
int nnumbers;
/* The caller made sure the const is a TSQuery, so get it now */
query = DatumGetTSQuery(constval);
stats = (Form_pg_statistic) GETSTRUCT(vardata->statsTuple);
/* MCELEM will be an array of TEXT elements for a tsvector column */
if (get_attstatsslot(vardata->statsTuple,
TEXTOID, -1,
STATISTIC_KIND_MCELEM, InvalidOid,
&values, &nvalues,
&numbers, &nnumbers))
{
/*
* There is a most-common-elements slot for the tsvector Var, so
* use that.
*/
selec = mcelem_tsquery_selec(query, values, nvalues,
numbers, nnumbers);
free_attstatsslot(TEXTOID, values, nvalues, numbers, nnumbers);
}
else
{
/* No most-common-elements info, so we must punt */
selec = (Selectivity) DEFAULT_TS_MATCH_SEL;
}
}
else
{
/* No stats at all, so we must punt */
selec = (Selectivity) DEFAULT_TS_MATCH_SEL;
}
return selec;
}
/*
* Extract data from the pg_statistic arrays into useful format.
*/
static Selectivity
mcelem_tsquery_selec(TSQuery query, Datum *mcelem, int nmcelem,
float4 *numbers, int nnumbers)
{
float4 minfreq;
TextFreq *lookup;
Selectivity selec;
int i;
/*
* There should be two more Numbers than Values, because the last two
* cells are taken for minimal and maximal frequency. Punt if not.
*/
if (nnumbers != nmcelem + 2)
return DEFAULT_TS_MATCH_SEL;
/*
* Transpose the data into a single array so we can use bsearch().
*/
lookup = (TextFreq *) palloc(sizeof(TextFreq) * nmcelem);
for (i = 0; i < nmcelem; i++)
{
/*
* The text Datums came from an array, so it cannot be compressed
* or stored out-of-line -- it's safe to use VARSIZE_ANY*.
*/
Assert(!VARATT_IS_COMPRESSED(mcelem[i]) && !VARATT_IS_EXTERNAL(mcelem[i]));
lookup[i].element = (text *) DatumGetPointer(mcelem[i]);
lookup[i].frequency = numbers[i];
}
/*
* Grab the lowest frequency. compute_tsvector_stats() stored it for us in
* the one before the last cell of the Numbers array. See ts_typanalyze.c
*/
minfreq = numbers[nnumbers - 2];
selec = tsquery_opr_selec(GETQUERY(query), GETOPERAND(query), lookup,
nmcelem, minfreq);
pfree(lookup);
return selec;
}
/*
* Traverse the tsquery in preorder, calculating selectivity as:
*
* selec(left_oper) * selec(right_oper) in AND nodes,
*
* selec(left_oper) + selec(right_oper) -
* selec(left_oper) * selec(right_oper) in OR nodes,
*
* 1 - select(oper) in NOT nodes
*
* freq[val] in VAL nodes, if the value is in MCELEM
* min(freq[MCELEM]) / 2 in VAL nodes, if it is not
*
*
* The MCELEM array is already sorted (see ts_typanalyze.c), so we can use
* binary search for determining freq[MCELEM].
*/
static Selectivity
tsquery_opr_selec(QueryItem *item, char *operand,
TextFreq *lookup, int length, float4 minfreq)
{
LexemeKey key;
TextFreq *searchres;
Selectivity selec, s1, s2;
/* since this function recurses, it could be driven to stack overflow */
check_stack_depth();
if (item->type == QI_VAL)
{
QueryOperand *oper = (QueryOperand *) item;
/*
* Prepare the key for bsearch().
*/
key.lexeme = operand + oper->distance;
key.length = oper->length;
searchres = (TextFreq *) bsearch(&key, lookup, length,
sizeof(TextFreq),
compare_lexeme_textfreq);
if (searchres)
{
/*
* The element is in MCELEM. Return precise selectivity (or at
* least as precise as ANALYZE could find out).
*/
return (Selectivity) searchres->frequency;
}
else
{
/*
* The element is not in MCELEM. Punt, but assert that the
* selectivity cannot be more than minfreq / 2.
*/
return (Selectivity) Min(DEFAULT_TS_MATCH_SEL, minfreq / 2);
}
}
/* Current TSQuery node is an operator */
switch (item->operator.oper)
{
case OP_NOT:
selec = 1.0 - tsquery_opr_selec(item + 1, operand,
lookup, length, minfreq);
break;
case OP_AND:
s1 = tsquery_opr_selec(item + 1, operand,
lookup, length, minfreq);
s2 = tsquery_opr_selec(item + item->operator.left, operand,
lookup, length, minfreq);
selec = s1 * s2;
break;
case OP_OR:
s1 = tsquery_opr_selec(item + 1, operand,
lookup, length, minfreq);
s2 = tsquery_opr_selec(item + item->operator.left, operand,
lookup, length, minfreq);
selec = s1 + s2 - s1 * s2;
break;
default:
elog(ERROR, "unrecognized operator: %d", item->operator.oper);
selec = 0; /* keep compiler quiet */
break;
}
/* Clamp intermediate results to stay sane despite roundoff error */
CLAMP_PROBABILITY(selec);
return selec;
}
/*
* bsearch() comparator for a lexeme (non-NULL terminated string with length)
* and a TextFreq. Use length, then byte-for-byte comparison, because that's
* how ANALYZE code sorted data before storing it in a statistic tuple.
* See ts_typanalyze.c for details.
*/
static int
compare_lexeme_textfreq(const void *e1, const void *e2)
{
const LexemeKey *key = (const LexemeKey *) e1;
const TextFreq *t = (const TextFreq *) e2;
int len1,
len2;
len1 = key->length;
len2 = VARSIZE_ANY_EXHDR(t->element);
/* Compare lengths first, possibly avoiding a strncmp call */
if (len1 > len2)
return 1;
else if (len1 < len2)
return -1;
/* Fall back on byte-for-byte comparison */
return strncmp(key->lexeme, VARDATA_ANY(t->element), len1);
}
src/backend/tsearch/ts_typanalyze.c
View file @ 4e57668d
......@@ -7,7 +7,7 @@
*
*
* IDENTIFICATION
* $PostgreSQL: pgsql/src/backend/tsearch/ts_typanalyze.c,v 1.1 2008/07/14 00:51:45 tgl Exp $
* $PostgreSQL: pgsql/src/backend/tsearch/ts_typanalyze.c,v 1.2 2008/09/19 19:03:40 tgl Exp $
*
*-------------------------------------------------------------------------
*/
......@@ -43,7 +43,9 @@ static void compute_tsvector_stats(VacAttrStats *stats,
static void prune_lexemes_hashtable(HTAB *lexemes_tab, int b_current);
static uint32 lexeme_hash(const void *key, Size keysize);
static int lexeme_match(const void *key1, const void *key2, Size keysize);
static int trackitem_compare_desc(const void *e1, const void *e2);
static int lexeme_compare(const void *key1, const void *key2);
static int trackitem_compare_frequencies_desc(const void *e1, const void *e2);
static int trackitem_compare_lexemes(const void *e1, const void *e2);
/*
......@@ -247,6 +249,7 @@ compute_tsvector_stats(VacAttrStats *stats,
int i;
TrackItem **sort_table;
int track_len;
int minfreq, maxfreq;
stats->stats_valid = true;
/* Do the simple null-frac and average width stats */
......@@ -273,7 +276,7 @@ compute_tsvector_stats(VacAttrStats *stats,
Assert(i == track_len);
qsort(sort_table, track_len, sizeof(TrackItem *),
trackitem_compare_desc);
trackitem_compare_frequencies_desc);
/* Suppress any single-occurrence items */
while (track_len > 0)
......@@ -287,6 +290,26 @@ compute_tsvector_stats(VacAttrStats *stats,
if (num_mcelem > track_len)
num_mcelem = track_len;
/* Grab the minimal and maximal frequencies that will get stored */
minfreq = sort_table[num_mcelem - 1]->frequency;
maxfreq = sort_table[0]->frequency;
/*
* We want to store statistics sorted on the lexeme value using first
* length, then byte-for-byte comparison. The reason for doing length
* comparison first is that we don't care about the ordering so long
* as it's consistent, and comparing lengths first gives us a chance
* to avoid a strncmp() call.
*
* This is different from what we do with scalar statistics -- they get
* sorted on frequencies. The rationale is that we usually search
* through most common elements looking for a specific value, so we can
* grab its frequency. When values are presorted we can employ binary
* search for that. See ts_selfuncs.c for a real usage scenario.
*/
qsort(sort_table, num_mcelem, sizeof(TrackItem *),
trackitem_compare_lexemes);
/* Generate MCELEM slot entry */
if (num_mcelem > 0)
{
......@@ -296,8 +319,15 @@ compute_tsvector_stats(VacAttrStats *stats,
/* Must copy the target values into anl_context */
old_context = MemoryContextSwitchTo(stats->anl_context);
/*
* We sorted statistics on the lexeme value, but we want to be
* able to find out the minimal and maximal frequency without
* going through all the values. We keep those two extra
* frequencies in two extra cells in mcelem_freqs.
*/
mcelem_values = (Datum *) palloc(num_mcelem * sizeof(Datum));
mcelem_freqs = (float4 *) palloc(num_mcelem * sizeof(float4));
mcelem_freqs = (float4 *) palloc((num_mcelem + 2) * sizeof(float4));
for (i = 0; i < num_mcelem; i++)
{
......@@ -308,12 +338,15 @@ compute_tsvector_stats(VacAttrStats *stats,
item->key.length));
mcelem_freqs[i] = (double) item->frequency / (double) nonnull_cnt;
}
mcelem_freqs[i++] = (double) minfreq / (double) nonnull_cnt;
mcelem_freqs[i] = (double) maxfreq / (double) nonnull_cnt;
MemoryContextSwitchTo(old_context);
stats->stakind[0] = STATISTIC_KIND_MCELEM;
stats->staop[0] = TextEqualOperator;
stats->stanumbers[0] = mcelem_freqs;
stats->numnumbers[0] = num_mcelem;
/* See above comment about two extra frequency fields */
stats->numnumbers[0] = num_mcelem + 2;
stats->stavalues[0] = mcelem_values;
stats->numvalues[0] = num_mcelem;
/* We are storing text values */
......@@ -379,25 +412,48 @@ lexeme_hash(const void *key, Size keysize)
static int
lexeme_match(const void *key1, const void *key2, Size keysize)
{
const LexemeHashKey *d1 = (const LexemeHashKey *) key1;
const LexemeHashKey *d2 = (const LexemeHashKey *) key2;
/* The keysize parameter is superfluous, the keys store their lengths */
return lexeme_compare(key1, key2);
}
/* The lexemes need to have the same length, and be memcmp-equal */
if (d1->length == d2->length &&
memcmp(d1->lexeme, d2->lexeme, d1->length) == 0)
return 0;
else
/*
* Comparison function for lexemes.
*/
static int
lexeme_compare(const void *key1, const void *key2)
{
const LexemeHashKey *d1 = (const LexemeHashKey *) key1;
const LexemeHashKey *d2 = (const LexemeHashKey *) key2;
/* First, compare by length */
if (d1->length > d2->length)
return 1;
else if (d1->length < d2->length)
return -1;
/* Lengths are equal, do a byte-by-byte comparison */
return strncmp(d1->lexeme, d2->lexeme, d1->length);
}
/*
* qsort() comparator for TrackItems - LC style (descending sort)
* qsort() comparator for sorting TrackItems on frequencies (descending sort)
*/
static int
trackitem_compare_desc(const void *e1, const void *e2)
trackitem_compare_frequencies_desc(const void *e1, const void *e2)
{
const TrackItem * const *t1 = (const TrackItem * const *) e1;
const TrackItem * const *t2 = (const TrackItem * const *) e2;
return (*t2)->frequency - (*t1)->frequency;
}
/*
* qsort() comparator for sorting TrackItems on lexemes
*/
static int
trackitem_compare_lexemes(const void *e1, const void *e2)
{
const TrackItem * const *t1 = (const TrackItem * const *) e1;
const TrackItem * const *t2 = (const TrackItem * const *) e2;
return lexeme_compare(&(*t1)->key, &(*t2)->key);
}
src/include/catalog/catversion.h
View file @ 4e57668d
......@@ -37,7 +37,7 @@
* Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
* $PostgreSQL: pgsql/src/include/catalog/catversion.h,v 1.486 2008/09/15 18:43:41 tgl Exp $
* $PostgreSQL: pgsql/src/include/catalog/catversion.h,v 1.487 2008/09/19 19:03:40 tgl Exp $
*
*-------------------------------------------------------------------------
*/
......@@ -53,6 +53,6 @@
*/
/* yyyymmddN */
#define CATALOG_VERSION_NO 200809151
#define CATALOG_VERSION_NO 200809191
#endif
src/include/catalog/pg_operator.h
View file @ 4e57668d
......@@ -8,7 +8,7 @@
* Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
* $PostgreSQL: pgsql/src/include/catalog/pg_operator.h,v 1.162 2008/08/16 00:01:37 tgl Exp $
* $PostgreSQL: pgsql/src/include/catalog/pg_operator.h,v 1.163 2008/09/19 19:03:40 tgl Exp $
*
* NOTES
* the genbki.sh script reads this file and generates .bki
......@@ -915,10 +915,10 @@ DATA(insert OID = 3630 ( "<>" PGNSP PGUID b f f 3614 3614 16 3630 3629 ts
DATA(insert OID = 3631 ( ">=" PGNSP PGUID b f f 3614 3614 16 3628 3627 tsvector_ge scalargtsel scalargtjoinsel ));
DATA(insert OID = 3632 ( ">" PGNSP PGUID b f f 3614 3614 16 3627 3628 tsvector_gt scalargtsel scalargtjoinsel ));
DATA(insert OID = 3633 ( "||" PGNSP PGUID b f f 3614 3614 3614 0 0 tsvector_concat - - ));
DATA(insert OID = 3636 ( "@@" PGNSP PGUID b f f 3614 3615 16 3637 0 ts_match_vq contsel contjoinsel ));
DATA(insert OID = 3637 ( "@@" PGNSP PGUID b f f 3615 3614 16 3636 0 ts_match_qv contsel contjoinsel ));
DATA(insert OID = 3660 ( "@@@" PGNSP PGUID b f f 3614 3615 16 3661 0 ts_match_vq contsel contjoinsel ));
DATA(insert OID = 3661 ( "@@@" PGNSP PGUID b f f 3615 3614 16 3660 0 ts_match_qv contsel contjoinsel ));
DATA(insert OID = 3636 ( "@@" PGNSP PGUID b f f 3614 3615 16 3637 0 ts_match_vq tsmatchsel tsmatchjoinsel ));
DATA(insert OID = 3637 ( "@@" PGNSP PGUID b f f 3615 3614 16 3636 0 ts_match_qv tsmatchsel tsmatchjoinsel ));
DATA(insert OID = 3660 ( "@@@" PGNSP PGUID b f f 3614 3615 16 3661 0 ts_match_vq tsmatchsel tsmatchjoinsel ));
DATA(insert OID = 3661 ( "@@@" PGNSP PGUID b f f 3615 3614 16 3660 0 ts_match_qv tsmatchsel tsmatchjoinsel ));
DATA(insert OID = 3674 ( "<" PGNSP PGUID b f f 3615 3615 16 3679 3678 tsquery_lt scalarltsel scalarltjoinsel ));
DATA(insert OID = 3675 ( "<=" PGNSP PGUID b f f 3615 3615 16 3678 3679 tsquery_le scalarltsel scalarltjoinsel ));
DATA(insert OID = 3676 ( "=" PGNSP PGUID b t f 3615 3615 16 3676 3677 tsquery_eq eqsel eqjoinsel ));
......
src/include/catalog/pg_proc.h
View file @ 4e57668d
......@@ -7,7 +7,7 @@
* Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
* $PostgreSQL: pgsql/src/include/catalog/pg_proc.h,v 1.514 2008/09/10 18:09:20 alvherre Exp $
* $PostgreSQL: pgsql/src/include/catalog/pg_proc.h,v 1.515 2008/09/19 19:03:40 tgl Exp $
*
* NOTES
* The script catalog/genbki.sh reads this file and generates .bki
......@@ -4434,7 +4434,11 @@ DESCR("GiST tsquery support");
DATA(insert OID = 3701 ( gtsquery_consistent PGNSP PGUID 12 1 0 0 f f t f i 5 16 "2281 2281 23 26 2281" _null_ _null_ _null_ gtsquery_consistent _null_ _null_ _null_ ));
DESCR("GiST tsquery support");
DATA(insert OID = 3688 ( ts_typanalyze PGNSP PGUID 12 1 0 0 f f t f s 1 16 "2281" _null_ _null_ _null_ ts_typanalyze _null_ _null_ _null_ ));
DATA(insert OID = 3686 ( tsmatchsel PGNSP PGUID 12 1 0 0 f f t f s 4 701 "2281 26 2281 23" _null_ _null_ _null_ tsmatchsel _null_ _null_ _null_ ));
DESCR("restriction selectivity of tsvector @@ tsquery");
DATA(insert OID = 3687 ( tsmatchjoinsel PGNSP PGUID 12 1 0 0 f f t f s 5 701 "2281 26 2281 21 2281" _null_ _null_ _null_ tsmatchjoinsel _null_ _null_ _null_ ));
DESCR("join selectivity of tsvector @@ tsquery");
DATA(insert OID = 3688 ( ts_typanalyze PGNSP PGUID 12 1 0 0 f f t f s 1 16 "2281" _null_ _null_ _null_ ts_typanalyze _null_ _null_ _null_ ));
DESCR("tsvector typanalyze");
DATA(insert OID = 3689 ( ts_stat PGNSP PGUID 12 10 10000 0 f f t t v 1 2249 "25" "{25,25,23,23}" "{i,o,o,o}" "{query,word,ndoc,nentry}" ts_stat1 _null_ _null_ _null_ ));
......
src/include/catalog/pg_statistic.h
View file @ 4e57668d
......@@ -8,7 +8,7 @@
* Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
* $PostgreSQL: pgsql/src/include/catalog/pg_statistic.h,v 1.36 2008/07/14 00:51:45 tgl Exp $
* $PostgreSQL: pgsql/src/include/catalog/pg_statistic.h,v 1.37 2008/09/19 19:03:41 tgl Exp $
*
* NOTES
* the genbki.sh script reads this file and generates .bki
......@@ -243,8 +243,12 @@ typedef FormData_pg_statistic *Form_pg_statistic;
* values. This is useful when the column datatype is an array or some other
* type with identifiable elements (for instance, tsvector). staop contains
* the equality operator appropriate to the element type. stavalues contains
* the most common element values, and stanumbers their frequencies, with the
* same rules as for MCV slots.
* the most common element values, and stanumbers their frequencies. Unlike
* MCV slots, the values are sorted into order (to support binary search
* for a particular value). Since this puts the minimum and maximum
* frequencies at unpredictable spots in stanumbers, there are two extra
* members of stanumbers, holding copies of the minimum and maximum
* frequencies.
*
* Note: in current usage for tsvector columns, the stavalues elements are of
* type text, even though their representation within tsvector is not
......
src/include/tsearch/ts_type.h
View file @ 4e57668d
......@@ -5,7 +5,7 @@
*
* Copyright (c) 1998-2008, PostgreSQL Global Development Group
*
* $PostgreSQL: pgsql/src/include/tsearch/ts_type.h,v 1.13 2008/07/14 00:51:45 tgl Exp $
* $PostgreSQL: pgsql/src/include/tsearch/ts_type.h,v 1.14 2008/09/19 19:03:41 tgl Exp $
*
*-------------------------------------------------------------------------
*/
......@@ -153,6 +153,9 @@ extern Datum ts_rankcd_wtt(PG_FUNCTION_ARGS);
extern Datum ts_rankcd_ttf(PG_FUNCTION_ARGS);
extern Datum ts_rankcd_wttf(PG_FUNCTION_ARGS);
extern Datum tsmatchsel(PG_FUNCTION_ARGS);
extern Datum tsmatchjoinsel(PG_FUNCTION_ARGS);
extern Datum ts_typanalyze(PG_FUNCTION_ARGS);
......
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